Studentship Vacancies

PhD Studentship Vacancies in Knowledge Media and Data Science

The success of our vibrant PhD student programme is due to a comprehensive support infrastructure and training provision that operates throughout our students' PhD programme. This includes a strong focus on community building and peer learning, weekly research forums, seminars, funding to participate in conferences, and an annual PhD student conference. Our PhD students have received best paper and distinguished dissertation awards at prestigious international conferences and have taken up research positions world-wide in academia, private companies (such as Google, Nokia and the BBC) and non-profit organisations.

We currently have a vacancy for a full-time PhD studentship based at The Open University in Milton Keynes starting on 1st October 2021, which includes a stipend of £15,285 per year.

The closing date for applications is: Wednesday, 31st March 2021 (5pm UK time)

Applicants are required to develop a project proposal as part of the application process and should contact the named contact(s) for their topic of interest to get more information and guidance on developing their application. Further details on the application process are available on the 'How to Apply' and 'Writing a PhD Proposal' pages.

The following list of topics, grouped by research area, are available this year.

Area 1. Blockchains and Decentralised Systems

  • Blockchain for Education

    This PhD project will investigate the potential of how Blockchain technology can transform education. For example supporting new forms of accreditation such as micro-credentials, Open Badges, reputation validation, ePortfolios, self-sovereignty for student data and radically new types of universities. Blockchain is the technology underlying crypto-currencies like Bitcoin, offering a publicly shared immutable ledger that can be used in many interesting and potentially revolutionary scenarios in education. For more information about our work, see

    Supervisors: Dr Alexander Mikroyannidis and Prof John Domingue

    Keywords: Blockchain Education Accreditation Micro-credentials Open Badges ePortfolios

    Skillset: Software development Education skills/interest Blockchain skills/interest

  • Blockchains and Decentralisation for Valuable Personal Data

    The over centralisation of data has led Tim Berners-Lee to call the Web 'anti-human'. This PhD will investigate how a combination of blockchain and decentralised data technologies (e.g. Solid) can be used to give users control of their own data whilst ensuring that others can still trust its contents, where it might otherwise be valuable to users to edit it. Educational qualifications are one example of this, but there are many others. This PhD will build on existing work where we have created a framework (LinkChains) for handling personal and sensitive data which combines decentralised data platforms with blockchain-based verification.

    Supervisors: Dr Allan Third and Prof John Domingue

    Keywords: Blockchain Decentralised Ledgers Linked Data Knowledge Graph Solid

    Skillset: Software and Web development Blockchain (especially Ethereum) Linked Data

  • Blockchains for Trustworthy Collaborative Agents

    Collaborative adaptation opportunistically composes the capabilities of multiple agents in unforeseen conditions to satisfy given requirements. However, this approach assumes that individual components will always behave as expected. This PhD project will investigate how to represent and reason about the capabilities of agents in a verified trustworthy fashion. This will include speculating and reasoning about their potential and recorded misbehaviour, and dynamically composing them in order to continue to satisfy requirements. The aim is to enable verifiably trustworthy collaboration in complex situations even when some agents fail or are malicious.

    Supervisors: Prof John Domingue and Dr Amel Bennaceur

    Keywords: Blockchain Adaptation Autonomous Agents Trust

    Skillset: Background in software development Background in distributed systems Background in blockchainsAn interest in automation and resilience

Area 2. Computational Social Science

  • AI and Digital Normativity

    To highlight useful trends and patterns, Artificial Intelligence (AI) technologies exploit norms. However, when applied to data about humans, this creates additional risks for communities that do not conform to societal norms, including those who are already marginalised. This PhD project will explore this very timely and important concern for the field of Ethical AI, in particular as AI for Social Good (and equivalents) have emerged to ensure that AI technology is applied to society's most pressing problems. The candidate will develop novel approaches for understanding digital normativity and its impacts, using a combinational of computational and social science methods.

    Supervisors: Dr Tracie Farrell and Dr Miriam Fernandez

    Keywords: Ethical AI AI for Social Good Sustainable Development Normativity Intersectionality

    Skillset: Mixed Methods research skills/interest Artificial Intelligence skills/interest Ethics and Justice skills/interest

  • Assessing and Mitigating the Impact of Global Phenomena, Geopolitical Factors, and Bias on Research

    The scientific enterprise is affected by global phenomena, such as the COVID-19 pandemic, geopolitical factors and different kinds of bias. This PhD project aims at shedding light on these issues and assessing their impact across gender, countries, disciplines and others. The main objective is to exploit large-scale datasets of scholarly knowledge, i.e., scientific knowledge graphs, to analyse collaboration, productivity, and other factors with the aim of understanding the extent of the phenomenon and identifying strategies to make scientific research more inclusive and resilient to external factors.

    Supervisors: Dr Angelo Salatino, Dr Francesco Osborne and Prof Enrico Motta

    Keywords: Scientometrics Scholarly Analytics Covid-19 Scholarly Data Semantic Web Science of Science Social Science Knowledge Graphs

    Skillset: Software Development Fast Prototyping Network Science Data Mining Data Integration Knowledge Graphs

  • Online misinformation

    Misinformation is compromising our ability to form informed opinions about various critical issues relating to politics, health, environment, and economy. This PhD can be focused on the use of computational methods to tackle any relevant topic, such as assessment of misinformation, tracking their spread across social media platforms, measuring and predicting their impact, and evaluating the effectiveness of various corrective measures on individuals and networks. This project will be performed in collaboration with several international projects and teams across Europe.

    Supervisors: Prof Harith Alani and Dr Gregoire Burel

    Keywords: Misinformation Social Media Data Science

    Skillset: Computer programming Machine Learning Social Network Analysis Large-Scale Data Analysis

  • Recommender Systems and the spread of online harm

    Recommender Systems have been pointed out as one of the major culprits of spreading online harm (misinformation, radical content, polarization) in the digital sphere. They are accused of promoting the creation of filter bubbles, lowering the diversity of information users are exposed to and the social contacts they create. This PhD will explore which particular types of recommender algorithms are more prone to recommend and spread harmful content, and if, and how, existing recommendation algorithms and evaluation metrics, can be modified or adapted to mitigate this spreading effect. This project will be conducted in collaboration with Universidad Autonoma de Madrid (UAM).

    Supervisors: Dr Miriam Fernandez, Dr Tracie Farrell and Dr Alejandro Bellojin (UAM)

    Keywords: Recommender Systems Social Media Online Harm

    Skillset: Programming Recommender Systems Machine Learning Social Network Analysis

Area 3. Data Science and Extended Intelligence

  • Affective interfaces for exploring biodiversity

    This topic will look at new affective ways to interact with photographs of animals and plants, such as those submitted to citizen science projects like Project suggestions include developing haptic touch interfaces to "feel" the different textures of nature, or methods to automatically categorise and browse collections of images of nature by textures and/or the emotions that they elicit in viewers. Research can be embedded into educational applications, including for schools.

    Supervisors: Dr Advaith Siddharthan and Prof Stefan Rueger

    Keywords: Affective Computing Haptics Image processing Natural language processing Biodiversity Citizen Science

    Skillset: Neural models for image and/or language processing Interest in Electronics or Interaction design

  • Knowledge Graphs for Cultural Heritage

    The project develops knowledge graphs of cultural content to be captured, analysed, and shared between heritage institutions, scholars, and the public. The candidate may focus on (a) innovative ways of exploring content such as artworks, books, and music; (b) innovative methods for extracting knowledge from unstructured resources (e.g. images, texts, and music). The PhD will benefit from being closely connected with two EU funded projects: SPICE which develops the novel paradigm of "citizen curation"; and Polifonia, devoted to building a knowledge graph of musical cultural heritage.

    Supervisors: Dr Enrico Daga and Dr Paul Mulholland

    Keywords: Linked Data Cultural Heritage Natural Language Processing

    Skillset: Software programming Knowledge Graphs Information Extraction Linked data

  • Predictive analytics and educational recommenders for students

    This PhD will focus on researching and developing novel Learning Analytic methods that can support students through their learning processes. A particular focus of this PhD will be the evaluation of the proposed solutions and their impact on students with historically low results, e.g. students from low socio-economic status. The PhD work will be closely related to OUAnalyse, an award-winning Learning Analytics system, currently deployed in more than 250 undergraduate modules at the OU.

    Supervisors: Dr Martin Hlosta, Dr Miriam Fernandez and Dr Christothea Herodotou (IET)

    Keywords: Learning Analytics Recommender Systems Attainment Gap Machine Learning Educational Technologies

    Skillset: Software Development EducationSkills/Interest Machine Learning

  • Supporting Scientific Research with Knowledge Graphs

    This PhD project aims at developing a new generation of intelligent systems for exploring and analysing the scientific literature with the goal of improving efficiency and verifiability of research. The traditional document-centric approaches for searching the literature do not scale to the large number of articles produced today. We aim to introduce a modern knowledge-centric solution by automatically extracting structured representations of research knowledge from very large repositories of research publications. The candidate will design novel approaches that exploit these knowledge graphs for answering complex queries on the literature, recommending articles, predicting emerging topics, and producing research hypotheses.

    Supervisors: Dr Francesco Osborne, Dr Angelo Salatino and Prof Enrico Motta

    Keywords: Knowledge Graphs Science of Science Data Science Deep Learning Scholarly Data Scholarly Analytics Information Extraction

    Skillset: Computer Programming Machine Learning Knowledge Graphs Interest/expertise in Research/Science

Area 4. New Media in Society

New Media and Society research aims at going beyond the study of Computing and ICT from a technology perspective, and looks at improving our understating human values and the impact of technology innovations on people's lives and their communities. This research particularly looks at ways to use new media to promote social justice and tackle complex societal challenges of inclusion and disadvantage.

  • Artificial Intelligence Systems for News Analysis and Media Agenda Monitoring

    This project aims to design novel AI techniques for multi-dimensional understanding and analysis of news. To this purpose, the candidate will develop novel approaches that will combine machine learning and natural language processing techniques for extracting a comprehensive semantic description of news content to support journalistic competence. The resulting knowledge graphs will enable the representation and reasoning over news frames to perform comparative analyses of media outlets, including viewpoints and biases. The candidate will focus on tasks such as news classification, prediction of news topics, monitoring event coverage, and agenda-setting analysis.

    Supervisors: Dr Enrico Daga, Dr Francesco Osborne and Prof Enrico Motta

    Keywords: Data Science News Analysis Deep Learning Knowledge Graphs Natural Language Processing Information Extraction

    Skillset: Computer programming Information extraction Knowledge graphs Interest/expertise in News and Media

  • Bias in AI models

    Advanced Artificial Intelligence (AI) models are used widely in the Financial Services Industry to make automated consumer decisions. Whilst the exercise typically follows a strict governance & ethical conduct, such models might still contain, or be likely to develop in iteration, hidden proxies or patterns related to protected consumer categories such as age ethnicity, disability, or religion, thus injecting undesired and undetected bias in their decisions. This PhD will investigate the use of data science methods for the automatic detection and removal of such patterns in AI applications used in the Financial Services Industry. The project will be performed in close collaboration with the Data Science Lab team from Visa Europe in London.

    Supervisors: Prof Harith Alani, Dr Miriam Fernandez and Dr Hasan Al-Madfaie (Head of Data Science Research, EU, Visa)

    Keywords: AI Algorithmic Bias Data Science Predictive Modelling

    Skillset: Data Science AI and machine learning Statistical modelling Semantic technologies (desirable)

  • Citizen Curation

    The aim of this project is to research and develop innovative user interfaces for Citizen Curation with which museum visitors can be guided in developing their own interpretations and responses to artworks, for example as online collections or stories. Citizen Curation aims to provide the public with ways of contributing their own perspective on culture as well as appreciating the perspective of others. The PhD will benefit from being closely connected to the EU funded SPICE project in which we are working closely with the Irish Museum of Modern Art (IMMA) in the development of a Citizen Curation case study.

    Supervisors: Dr Paul Mulholland and Dr Enrico Daga

    Keywords: Human Computer Interaction Cultural Heritage Technology enhanced learning

    Skillset: HCI design and evaluation Web programming (e.g. Java, PHP, Python)

  • Improving Citizen Participation in the Climate Debate with Multimedia Deliberation Technologies

    The public is increasingly worried about climate change, especially young generations are concerned about their future on this planet and seek new ways to be engaged in a more democratic inclusive discussion about climate action. Still, technology for citizen engagement and online deliberation of climate change issues are either very simple (such as social media) but inappropriate to support heathy and effective deliberation, or too complex (such as as Kialo, Deliberatorium, DebateGraph, The Evidence Hub), and therefore, hardly inclusive and adopted at scale. This PhD research aims at improving accessibility of large-scale online discussion platforms by providing novel features for voice-to-text translation and multimedia contribution to the online debate (in form of audio and video file). This will enable participants to use oral and gestural communication to engage with climate debates, thus promoting participation from younger and/or less digitally savvy communities (which usually are less at ease with written communication).

    Supervisors: Anna De Liddo

    Keywords: Online Deliberation Climate Change large scale argumentation multimedia interaction voice-to-text systems

    Skillset: Programming (Web Development, Python) Statistics

  • Novel Technology to Support Social Activism

    This project aims to design novel technologies, including ubiquitous and social media, to support activism and social justice towards some Sustainable Development Goals (SDGs). The candidate will work in between social sciences and technology design and development, conducting user-centred activities such as interviews, workshops and participatory design sections. It is also expected that the candidate will engage with local communities, charity organisations and schools and will pilot technical solutions using sensors and social media.

    Supervisors: Dr Lara Piccolo, Dr Tracie Farrell

    Keywords: Technology for Social Changes SDGs Human-Computer Interaction

    Skillset: Computer programming Interest/expertise in user-centred methods Interest in social activism

  • Real-Time Multimedia Interaction Technologies to Reduce Social Polarisation

    Political instability and conflict plague the world. Peace building education is becoming more than a call, it is a paramount civic skill that any 21st century citizen should learn to practice. Still, there is a growing distrust toward our human capability to 'change our mind', and develop social empathy toward people that we perceive as "different from us". This PhD research focuses on multimedia narrative interaction technologies as means for people to reflect, think critically and challenge personal bias. Building on our research on Democratic Reflection the successful candidate will improve and test the capability of this technology to promote critical thinking and reduce polarization of opinions in highly dividing contexts (such as post-war or political unrest scenarios). Changing assumptions is a crucial skill to promote social tolerance and build peace in our divided society, this PhD will investigate the theories, methods and tools to enable it.

    Supervisors: Anna De Liddo

    Keywords: Real-Time Audience Interaction Multimedia Storytelling Critical Thinking

    Skillset: Programming (Web Development, Python) Statistics

  • Tools for discussion and collaboration in distance learning

    While asynchronous approaches to distance learning in higher education support flexible forms of study, they can limit the level of student's interaction with other students and their lecturers. This project will develop and evaluate the use of synchronous (i.e. real time) approaches to promote active learning through discussion and collaboration as part of a blended approach to distance learning. This is likely to involve the integration of communication technologies (e.g. web conferencing, web broadcasting, instant messaging and online polling) with collaborative learning and teaching strategies (e.g. team-based learning, think-pair-share, problem-based learning, peer teaching, peer assessment).

    Supervisors: Dr Trevor Collins

    Keywords: Distance Learning Technology Enhanced Learning Learning Design

    Skillset: Interest/experience in distance education or online learning Participatory design Web development Training/experience of research methods Interest/experience in educational evaluation


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